Fraud detection platform for social connection and claim history analysis

Data as of Oct 25, 2026Reviewed by

How we measure

Which brands AI mentions

#BrandMentioned in
=1SAS Fraud Decisioning for Claims51%
=1DataWalk43%
=3FRISS34%
=3Quantexa26%
=3Shift Technology21%

Mentioned in · Jul 5 – Oct 25, 2026

ChatGPT SearchChatGPT SearchGoogle AI ModeGoogle AI Mode

Widest split: SAS Fraud Decisioning for Claims, 79% on ChatGPT Search and 22% on Google AI Mode.

  • =1SAS Fraud Decisioning for ClaimsChatGPT Search 79%Google AI Mode 22%
  • =1DataWalkChatGPT Search 25%Google AI Mode 61%
  • =3FRISSChatGPT Search 21%Google AI Mode 48%
  • =3QuantexaChatGPT Search 33%Google AI Mode 17%
  • =3Shift TechnologyChatGPT Search 13%Google AI Mode 30%

Questions and answers

  • ChatGPT SearchOct 15, 2026

    1. 1Verisk ClaimSearch
    2. 2SAS Fraud Framework for Insurance
    3. 3Quantexa
    4. 4DataWalk
    5. 5Verisk Claim Scoring

    The type of platform you're looking for is an AI-powered fraud detection platform with social network analysis and historical claims intelligence. It connects people, providers, addresses, previous claims, and other shared identifiers to detect suspicious relationships and flag potentially fraudulent claims before payment is released.

    For insurance claims, two key capabilities to look for are network analysis (finding connected fraud rings) and predictive risk scoring (ranking claims for review before settlement).

    Platforms worth evaluating

    • Claims Scoring detects fraud quickly and accurately | Verisk

    1. Verisk ClaimSearch and Claim Scoring

    (Strong for insurance claims)

    Connects claims across insurers to surface repeat losses, shared parties, prior claim history, and suspicious patterns. Predictive scoring helps prioritize claims for investigation.

    Website:

    • SAS Payment Integrity for Health Care | SAS

    2. SAS Fraud Framework for Insurance

    Combines historical data, social network analysis, anomaly detection, and near-real-time claim scoring to uncover linked entities and potential fraud rings before settlement.

    Website:

    • Quantexa - Redefine Decision-Making | Quantexa

    3. Quantexa Insurance Fraud

    Uses entity resolution and graph analytics to connect seemingly unrelated people, organizations, and transactions, with real-time risk analysis to support payment decisions.

    Website:

    • Insurance Fraud Detection & Investigation Software | DataWalk

    4. DataWalk

    Combines link analysis, clustering, rules, and predictive models to help investigators identify suspicious networks and understand why a claim was flagged.

    Website:

    Which one should you choose?

    My starting recommendation is Verisk if you're an insurer looking for established claims-history matching, or SAS if you need broader, configurable fraud analytics and network analysis. Quantexa is also worth evaluating for complex, connected fraud schemes.

    One important distinction: if by “social connections” you mean public social-media profiles rather than relationships among claimants, providers, and previous claims, the right platform may be different.

    What type of fraud are you trying to prevent?

    1. Industry

    Insurance claims (auto, property, health)

    Healthcare payments and provider fraud

    Government benefits or public assistance

    E-commerce, refunds, or payment fraud

    Other claims or payouts

    2. What connections should it analyze?

    People, providers, and historical claims

    Social media and online identities

    Transactions, accounts, and payment networks

    All of the above

    3. Organization size

    Small or mid-sized business

    Large insurer or enterprise

    Government or public agency

    [Find the best-fit platform]

    Sources cited in this answer5

    Google AI ModeOct 15, 2026

    1. 1Shift Technology
    2. 2FRISS
    3. 3Web-IQ
    4. 4DataWalk
    5. 5SAS Fraud Decisioning for Claims
    6. 6DataWalk Insurance Fraud Detection & Investigation Software
    7. 7SAS Social Network Analysis

    Several enterprise AI and fraud analytics platforms specialize in cross-referencing social connections, relationship mapping, and historical claim data to flag organized or opportunistic fraud before a payout is made.

    Top platforms providing these capabilities include:

    • Shift Technology – Known for its AI-native Insurance Data Network and advanced network detection. It maps entity resolution (identifying hidden name variations or aliases), identity links (shared phone numbers, IP addresses, or device IDs), and cross-carrier history to surface organized fraud rings that look like completely unrelated, normal claims on the surface.
    • FRISS – Offers real-time AI-powered Claims Analytics that automatically evaluate risk indicators, individual loss history, and social/online network connections (such as integration with Web-IQ to spot hidden ties between claimants, witnesses, or third parties) before payment approval.
    • DataWalk – Provides enterprise-scale Insurance Fraud Detection & Investigation Software that unifies internal CRM records, external data, and social network analysis. It visually maps relationships between claimants, repair shops, medical providers, and historical records to highlight suspicious clusters.
    • SAS Fraud Decisioning for Claims – Utilizes embedded AI, anomaly detection, and a dedicated Social Network Analysis component to score claims at first submission and rescore them across processing stages by mapping complex networks of related activities.

    If you'd like to narrow this down, please let me know:

    • What line of insurance or industry (e.g., auto, property, workers' comp, health) you are operating in
    • Whether you need a solution that integrates with a specific core claims system (like Guidewire or Duck Creek)

    I can help you compare implementation scope or pricing models for these options.

    Sources cited in this answer9

  • Google AI ModeOct 25, 2026

    1. 1Verisk ClaimSearch
    2. 2Shift Technology
    3. 3FRISS
    4. 4SAS Insurance Fraud

    To prevent fraudulent payouts, several enterprise-grade platforms specialize in analyzing historical cross-industry claim databases, relational data, and digital/social networks to flag suspicious behavior before funds are ever issued.

    Top platforms offering these capabilities include:

    • Verisk ClaimSearch
      • Core Strength: Operates the largest property and casualty (P&C) claims database in the industry, capturing over 95% of insured carrier claim data with over a billion records.
      • How it spots red flags: It uses advanced link analysis, automated image anomaly detection (digital media forensics), and predictive claim scoring to reveal hidden relationships and organized fraud rings among claimants, medical providers, and past losses before you approve payment.
    • Shift Technology (Fraud & Risk)
      • Core Strength: A cloud-native, AI-driven platform built explicitly for insurance and claims fraud detection.
      • How it spots red flags: Its Insurance Data Network (IDN) uncovers complex multi-carrier schemes by analyzing external data sources, documents, and behavioral indicators. It provides high explainability scoring—showing investigators exact reason codes and connections at First Notice of Loss (FNOL).
    • FRISS
      • Core Strength: Automated trust and fraud analytics for P&C insurers with fast real-time claim scoring.
      • How it spots red flags: FRISS features integrated online network analysis (via partner tech like Web-IQ) that automatically cross-references public and online environments to identify if claimants, witnesses, and vendors share hidden or suspicious digital connections. It also includes AI-driven media checks to flag manipulated or deepfake damage photos.
    • SAS Insurance Fraud
      • Core Strength: Enterprise-scale machine learning and social network analysis.
      • How it spots red flags: SAS maps out entity relationships (connecting claimants, garages, doctors, and addresses) to uncover covert crime rings and unusual associations over time, reducing false positives while surfacing actionable investigation dossiers.

    To help narrow down the best fit, could you share:

    • What line of business (e.g., auto, property, health/liability) you operate in?
    • Roughly how many claims your team processes per month?

    Sources cited in this answer10

    ChatGPT SearchOct 25, 2026

    1. 1SAS
    2. 2Shift Technology
    3. 3Carpe Intel
    4. 4SAS Fraud Decisioning for Claims

    For what you describe, I’d focus on AI-powered claims fraud detection platforms that combine historical claim analysis, social network analysis, and pre-payment risk scoring. These systems look beyond an individual claim to identify repeat claimants, suspicious relationships between people or providers, and patterns associated with coordinated fraud.

    Three particularly relevant options are SAS, Shift Technology, and Carpe Intel. They serve somewhat different needs, especially when deciding whether you need enterprise-wide claims analytics, cross-carrier fraud intelligence, or social-media investigations.

    Platforms worth evaluating

    • Fraud Awareness & Prevention: What it is and why it matters | SAS

    1. SAS Fraud Decisioning for Claims

    (Strong functional match)

    Best for organizations needing to flag suspicious claims before payment using historical claims, anomaly detection, risk scores, and relationship mapping.

    • Scores claims at submission and during processing.
    • Identifies suspicious connections across claimants, providers, and claims.
    • Supports investigation workflows and explainable alerts.

    Website:

    2. Shift Technology

    Best for insurers looking to detect organized fraud rings and combine internal claims records with external intelligence.

    • Analyzes historical claims, documents, and external data sources, including social media data through its data integrations.
    • Maps relationships among people and providers.
    • Produces prioritized fraud alerts with supporting explanations.

    Website:

    • Carpe | The AI-Native Decision Platform for Insurance

    3. Carpe Intel

    Best for claims teams that specifically need to investigate claimants' public online presence and social connections.

    • Searches public social profiles, public records, news, and other online sources.
    • Highlights inconsistencies between online evidence and claim details.
    • Generates risk scores and evidence-linked investigation reports.

    Website:

    Which should you shortlist?

    Your main requirementPlatform to evaluate first
    Automated pre-payment scoring plus claims network analysisSAS
    Insurance-specific AI and connected fraud-ring detectionShift Technology
    Social-media research and claimant-level investigationsCarpe Intel

    These are capability-based matches, not independently verified performance rankings. Confirm the precise features, integrations, and pricing with each vendor.

    What to require in a vendor demo

    Ask each provider to demonstrate the following using representative historical claims:

    • Historical matching: Does it find repeat claims, linked identities, shared addresses, and suspicious provider patterns?
    • Social intelligence: Can it analyze relevant public social-media information and connect it to verified claim facts?
    • Pre-payment controls: Can a risk score trigger a payment hold or investigator review before funds are released?
    • Explainability: Does each alert show the underlying evidence, source, and reason for the flag?
    • Accuracy and compliance: What are the false-positive rate, detection rate, audit capabilities, and applicable privacy restrictions?

    Treat a risk flag as a reason to investigate, not proof of fraud. Keep final payment decisions subject to appropriate human review and applicable law.

    One question to narrow this down

    What type of claims are you trying to protect against fraud?

    1. Claim type

    Insurance claims (auto, property, injury, etc.)

    Healthcare or medical reimbursement claims

    Government benefits or assistance payments

    Warranty, reimbursement, or customer refund claims

    Other

    2. Most important capability

    Historical claims and fraud-ring detection

    Social-media and online investigations

    Both, with pre-payment risk scoring

    3. Organization size

    Small team or business

    Mid-sized organization

    Large enterprise or insurer

    [Find the best-fit platform]

    Sources cited in this answer10

Also asked as

  • I am looking for a fraud detection tool that can review claim history and social connections to identify suspicious activity prior to issuing payments.